So I guess I see two questions.
The first is to “help people park their car in safer neighborhoods / better times in the day”. Algorithm itself doesn’t track locations/instances, produce data out of nowhere. But I am sure there are publicly available sources having those data, such as police authority posting crime data, with the time and location that each instance happened. In fact, I found a this website does a beautiful visualization on car break-ins in SF. https://projects.sfchronicle.com/trackers/sf-car-breakins/
The second is to find the real reasons behind higher break-ins, maybe it’s higher number of homeless people on the road, maybe it’s because the unemployment rate goes up, or maybe it’s even because people are buying better cars, you don’t know, but you could come up with hypothesis and use data to validate your hypothesis. If your model is accurate, you could do prediction tasks, something like given these features, what would be the number of break-ins happening next month? It could have applications in insurance industry I believe.